Reliability Model of Medical Equipment in University of Port Teaching Hospital

  • N. P. Akpan Department of Mathematics and Statistics, University of Port Harcourt, Nigeria
  • E. R. Anyi-Akparanta Department of Mathematics and Statistics, University of Port Harcourt, Nigeria
Keywords: reliability, Weibull distribution, maintainability, exponential distribution, University of Port Harcourt Teaching Hospital


In this research, on medical equipment maintainability and reliability we conducted basic statistics analysis using University of Port Harcourt Teaching Hospital as the case study; the data collected covered 18 departments, namely; Anatomical Pathology, Micro Biology, Chemical Pathology Laboratory, Radiography Department, Pediatrics, Hemodialialysis, Hematology and Blood Transfusion, Physiotherapy, Dental Department, MDR-TB unit, Pharmacy, ICU, Assisted Conception Unit, Orthopedic Ward, Care for Elderly Laboratory, Family Planning Unit, Community Medicine and Labour Ward. The results of the parametric Weibull distribution percentile suggested that the reliability of the devices tends to fail every 21 days. The reliability plot of the model indicated that the devices tend to decrease its life span with age, the Weibull model was adequately fitted following the results of Anderson adjust test of goodness of fit and the probability plot. In comparison, the Probability value of goodness of fit P(0.0000) of Weibull distribution model was compared  with that of exponential distribution model P(0.034), the outcome showed that Weibull distribution is better to model the data of medical equipment in University of Port Harcourt Teaching Hospital.


Shamayleh, A., Awad, M., & Farhat, J. (2020). IoT based predictive maintenance management of medical equipment. Journal of Medical Systems, 44, Article No. 72.

Campbell, J. D., & Jardine, A. K. S. (2001). Maintenance excellence: Optimizing equipment life-cycle decisions. New York: Marcel Dekker.

Cheng, M., & Dyro, J. F. (2004). Good management practice for medical equipment. In J. F. Dyro (Ed.), Clinical engineering handbook (pp. 108-110). San Diego: Elsevier.

Fennigkoh, L., & Smith, B. (1989). Clinical equipment management. JCAHO Plant, Technology, and Safety Management Series, 2, 5-14.

Garmabaki, A. H. S., Ahmadi, A., Block, J., Pham, H., & Kumar, U. (2016). A reliability decision framework for multiple repairable units. Reliability Engineering & System Safety, 150, 78-88.

Rice, W. (2007). Medical device risk based evaluation and maintenance using fault tree analysis. Biomedical Instrumentation and Technology, 41(1), 76-82.

Ridgway, M. (2001). Classifying medical devices according to their maintenance sensitivity: a practical, risk-based approach to PM program management. Biomedical Instrumentation and Technology, 35(3), 167-176.

Stiefel, R. H. (2009). Medical equipment management manual (7th ed.). Annapolis Junction, MD: AAMI.

University of Michigan Hospitals (2010). Equipment Management Plan 2010. Retrieved from

Wang, B. (2006). Fennigkoh and Smith model for inclusion criteria: 15-year retrospective. Journal of Clinical Engineering, 31(1), 26-30.

Wang, B., & Levenson, A. (2000). Equipment inclusion criteria- a new interpretation of JCAHO’s medical equipment management standard. Journal of Clinical Engineering, 25(1), 26-35.

World Health Organization (1998). District Health Facilities, Guidelines for Development and Operations. WHO Regional Publications, Western Pacific Series, No. 22.

Younger (2010). Healthcare institutions are capable of optimizing maintenance costs, enhancing monitoring activities, managing maintenance tasks with available workforces and resources. Retrieved from

How to Cite
Akpan, N. P., & Anyi-Akparanta, E. R. (2024). Reliability Model of Medical Equipment in University of Port Teaching Hospital. Earthline Journal of Mathematical Sciences, 14(3), 459-475.